Methods and apparatus to detect commercial advertisements associated with media presentations

ABSTRACT

Methods and apparatus to detect commercial advertisements associated with media presentations are disclosed. An example method involves receiving a video frame and detecting a change in box-formatting between the video frame and a subsequent video frame. A transition between the video frame and the subsequent video frame is indicated as a commercial advertisement transition based on the detected change in box-formatting.

RELATED APPLICATIONS

This patent arises from a continuation of U.S. patent application Ser.No. 16/851,997, filed on Apr. 17, 2020, now U.S. Pat. No. 11,070,871,which is a continuation of U.S. patent application Ser. No. 16/012,413,filed on Jun. 19, 2018, now U.S. Pat. No. 10,631,044, which is acontinuation of U.S. patent application Ser. No. 15/449,160, filed onMar. 3, 2017, now U.S. Pat. No. 10,028,014, which is a continuation ofU.S. patent application Ser. No. 14/554,268, filed on Nov. 26, 2014, nowU.S. Pat. No. 9,591,353, which is a continuation of U.S. patentapplication Ser. No. 12/827,701, filed on Jun. 30, 2010, now U.S. Pat.No. 8,925,024, which claims the benefit of U.S. Provisional PatentApplication No. 61/291,735, filed on Dec. 31, 2009. U.S. patentapplication Ser. No. 16/851,997, U.S. patent application Ser. No.16/012,413, U.S. patent application Ser. No. 15/449,160, U.S. patentapplication Ser. No. 14/554,268, U.S. patent application Ser. No.12/827,701, and U.S. Provisional Patent Application No. 61/291,735 arehereby incorporated by reference herein in their entireties.

FIELD OF THE DISCLOSURE

The present disclosure relates generally to monitoring media and, moreparticularly, to methods and apparatus to detect commercialadvertisements associated with media presentations.

BACKGROUND

Advertisers are often interested in knowing whether their advertisementsoccurred and were placed as expected. Confirming the occurrence andplacement of advertisements can be used for market research purposes,billing purposes, and advertisement campaign planning purposes. Suchadvertisements may be in the form of television advertisements or othervideo/audio advertisements including Internet streaming advertisements.Depending on the conveyance medium (e.g., print, radio, television,computer, etc.) used for advertising, different known techniques can beused to confirm the presentation of advertisements in those media.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a digital television broadcast environment.

FIG. 2 depicts a television program feed provided by a media contentprovider of FIG. 1 .

FIG. 3 depicts a commercial advertisement feed provided by an advertiserof FIG. 1 and a box formatting process performed on the commercialadvertisement.

FIG. 4 depicts an example spliced television program and boxedcommercial advertisement generated by a network television broadcasteror media content provider of FIG. 1 .

FIG. 5 depicts another example type of spliced television program andboxed commercial advertisement generated by a network televisionbroadcaster or media content provider of FIG. 1 .

FIG. 6 depicts another example type of spliced television program andboxed commercial advertisement generated by a network televisionbroadcaster or media content provider of FIG. 1 .

FIG. 7 depicts video and audio portions of an example spliced programand advertisement generated by the network television broadcaster ofFIG. 1 .

FIG. 8 depicts a time-based audio waveform of non-random audio that canaccompany inter-scene blank frames within a program segment of a digitaltelevision feed.

FIG. 9 depicts a time-based audio waveform of random audio that canaccompany commercial-transition blank frames between program segments ofa digital television feed.

FIG. 10 depicts an example apparatus that can be used to detectcommercial advertisements in digital television feeds.

FIG. 11 is a flow diagram representative of example machine readableinstructions that can be executed to detect commercial advertisements indigital television feeds based on monitoring video frames.

FIG. 12 is a flow diagram representative of example machine readableinstructions that can be executed to detect commercial advertisements indigital television feeds based on monitoring audio frames.

FIG. 13 is a flow diagram representative of example machine readableinstructions that can be executed to perform random audio analyses inconnection with the example process of FIG. 12 .

FIG. 14 is a flow diagram representative of example machine readableinstructions that can be executed to perform weighted hint analyses inconnection with the example processes of FIGS. 11 and 12 to confirmcommercial advertisement transitions in digital television feeds.

FIG. 15 is an example processor system that can be used to execute theexample instructions of FIGS. 11, 12, 13 , and/or 14 to implement theexample apparatus of FIG. 10 .

DETAILED DESCRIPTION

Although the following discloses example methods, apparatus, systems,and articles of manufacture including, among other components, firmwareand/or software executed on hardware, it should be noted that suchmethods, apparatus, systems, and articles of manufacture are merelyillustrative and should not be considered as limiting. For example, itis contemplated that any or all of these hardware, firmware, and/orsoftware components could be embodied exclusively in hardware,exclusively in firmware, exclusively in software, or in any combinationof hardware, firmware, and/or software. Accordingly, while the followingdescribes example methods, apparatus, systems, and articles ofmanufacture, the examples provided are not the only ways to implementsuch methods, apparatus, systems, and articles of manufacture.

The example methods, apparatus, and articles of manufacture describedherein can be used to detect commercial advertisements associated withmedia presentations (e.g., in television transmission feeds). Althoughthe example methods, apparatus, and articles of manufacture aredescribed herein in connection with detecting commercial advertisementtransitions in digital television transmission feeds, the examplemethods, apparatus, and articles of manufacture may also be used todetect commercial advertisement transitions in analog televisiontransmission feeds and/or in other types of audio/video media includingInternet-based media transmissions, video on demand media transmissions,remotely stored media for time-shifted media transmission, mediatransmissions stored locally for time-shifted viewing, etc.

Commercial detection can be used to identify placements of commercialadvertisements in television program content and can be used as thebasis for further identification processes to determine which specificcommercials were presented at particular times. Such commercialdetection and identification processes can be used to confirm thatcommercial advertisements were correctly presented and placed atpre-selected points of television program presentations or withinpre-selected (e.g., contracted for) daytime or nighttime slots. Inaddition, such commercial detection and identification processes canalso be used to identify when audience members are exposed to commercialadvertisements during television program viewings. Television programscan be, for example, movies, sit-coms, dramas, television mini-series,etc. regardless of broadcast medium (e.g., terrestrial, satellite, radiofrequency (RF), cable, etc.).

To facilitate commercial detection in digital television transmissions(and/or analog television transmissions), the methods, apparatus, andarticles of manufacture described herein detect features orcharacteristics in digital television transmission feeds (and/or analogtelevision transmissions) to identify transitions between a televisionprogram and a commercial advertisement and between different commercialadvertisements. In this manner, commercial advertisements can bedistinguished from television program content and commercialadvertisements can also be distinguished from one another. Examplefeature/characteristic detection schemes to identify program/commercialtransitions, commercial/commercial transitions, or commercial/programtransitions include profile change detection and random audio detection,which are described in detail herein.

Although not necessary, in some example implementations, theprogram/commercial, commercial/commercial, and commercial/programtransition detection techniques described herein can be used to triggersignature generation processes, watermark detection/collectionprocesses, and/or ancillary code detection/collection processes. In thismanner, when a transition is detected, a media detection process can betriggered to generate signatures of media content, detect/collectwatermarks in media content, and/or detect/collect ancillary codes(e.g., audio or video codes embedded into the media content and/or inwatermarks in the media content) from the media content to identify adisplayed commercial advertisement (in the case of a program/commercialtransition or a commercial/commercial transition) or a displayedtelevision program (in the case of a commercial/program transition). Insuch example implementations, the collected signatures, watermarkinformation, and/or codes can be time-stamped to form a timelineindicative of when television program segments occurred and whencommercial advertisements occurred in broadcast digital televisiontransmissions. In other example implementations, any other techniquesmay be used to identify displayed commercial advertisements in responseto detecting commercial transitions as described herein.

Profile change detection involves detecting changes in useable andnon-useable display areas of displayed video frames as a digitaltelevision program is decoded and video frames are reconstructed. Auseable display area is the portion(s) of a video frame used to displayvideo content that is relevant to and/or part of a media presentation ona screen. In contrast, non-useable display areas are portion(s) of avideo frame that are displayed on a screen but that do not displayrelevant video content (e.g., video content that is relevant to and/orpart of a media presentation on a screen). For example, non-useabledisplay areas (or screen filler areas) can display black bars, graybars, static network logo images, etc. that are not part of the primarycontent being displayed in the useable display areas. Such non-useabledisplay areas may result from box formatting techniques used to adaptmedia content for presentation on television screens having differentaspect ratios from the aspect ratios of the media content.

Common box formatting techniques include a pillarbox format, a letterboxformat, and a windowbox format. Pillarbox formatting results innon-useable display areas (e.g., blank areas or static image areas) onthe left and right sides bordering a useable display area. Letterboxformatting results in non-useable display areas on the top and bottomportions bordering a useable display area. Windowbox formatting resultsin non-useable display areas on the left and right sides and the top andbottom portions bordering a useable display area such that the useabledisplay area appears embedded within an all-surrounding frame (or matborder) when displayed on a television.

In digital television broadcasting, box formatting may be used when theaspect ratio of a television program is different from the aspect ratioof a commercial advertisement that is inserted between different programsegments of a television program. For example, if a television programis produced using a 16:9 aspect ratio (e.g., a widescreen displayprofile) and a commercial advertisement is produced using a 4:3 aspectratio (e.g., a full-screen display profile), a network televisionbroadcaster can adapt the commercial advertisement using a pillarboxformat for insertion into the television program while maintaining acontinuous 16:9 aspect ratio even between program/commercialtransitions. In this manner, the resulting broadcasted digitaltelevision feed can be broadcast in its entirety using the 16:9 aspectratio so that the broadcaster need not intermittently change thebroadcasted aspect ratio when transitioning between program content andcommercial advertisements. In some example implementations, boxformatting changes can also occur when a television program is boxformatted and a commercial advertisement is not. This can occur when atelevision program is not produced in a native 16:9 widescreen digitaltelevision format and a commercial advertisement is so formatted. Bymonitoring box formatting characteristics of a digital television feed,the methods, apparatus, and articles of manufacture described herein cangenerate information indicating that a possible commercial transitionhas been detected when the profile change detection techniques detect achange in the appearance of useable/non-useable display areas.

Random audio detection involves detecting audio frames having mostlyrandom noise. Such random-noise audio frames can be indicative oftransitions between program segments and commercial advertisements andtransitions between different commercial advertisements. In digitaltelevision transmission feeds, when a broadcaster inserts commercialadvertisements in different parts of a television program, the insertionprocess may also insert commercial transition video and audio framesbetween the television program frames and commercial advertisementframes. Such commercial transition frames typically exhibit some form ofblank-like or silence-like (e.g., quiet audio) features orcharacteristics. These silence-like audio characteristics, which resultfrom the process of splicing-in commercial advertisements, are typicallynot complete or absolute silence. Instead, although typicallyunintentional on the part of the broadcasters, the commercial transitionframes often exhibit random noise characteristics that produce hiss-likeaudio due to several factors such as, for example, over-amplification.

The example methods, apparatus, and articles of manufacture describedherein use the random noise characteristics of commercial transitionaudio frames to distinguish commercial transition audio frames fromscene-change audio frames that also exhibit silence-like characteristics(e.g., near-silent or quiet audio) to indicate scene transitions withinthe same program segment. That is, the methods, apparatus, and articlesof manufacture described herein can distinguish between commercialtransition audio frames and scene transition audio frames based on theamount of audio randomness of each type of audio frame. While commercialtransition audio frames exhibit a high level of random audio due to thecommercial splicing process described above, scene transition audioframes exhibit relatively lower or no random audio characteristics. Forexample, because scene transition frames transition between contentoriginally belonging to the same program, the audio content of thetransition frames is relatively smoother or more continuous becausethere is no splicing disruption. Also, media content producers canintentionally insert background tones or other sounds in scenetransition frames to produce a flowing effect or provide audiblyperceptible continuity between scenes. Such background tones or otherintentionally inserted sounds exhibit very low or no randomcharacteristics whatsoever. In the illustrated examples describedherein, commercial transition frames are identified as those frameshaving audio that exhibits a randomness factor exceeding a specifiedrandomness threshold.

In the illustrated examples described herein, the feature/characteristicdetection schemes (e.g., profile change detection and/or random audiodetection) are used to generate commercial transition hints. Such hintsare indications that a transition to a commercial advertisement may haveoccurred in a monitored digital television feed. When two or moredifferent feature/characteristic detection techniques are used in acommercial detection system, such hints can be advantageously used incombination with a voting scheme to confirm occurrences of commercialadvertisement transitions. For example, if a commercial detection systemuses both profile change detection and random audio detection, each ofthe detection processes can concurrently generate a respective hintvalue (e.g., hint=1.0) when a commercial transition is suspected. Eachof the two hint values can then be weighted based on the reliability(e.g., historical reliability or robustness) of their respectiveprocesses, and the weighted hint values can be aggregated to generate aweighted aggregate hint value. If the weighted aggregate hint valueexceeds a specified threshold hint value, a commercial transition can beconfirmed.

Although the example methods, apparatus, and articles of manufacture aredescribed herein in detail in connection with profile change detectionand/or random audio detection, commercial transition hints and theiranalyses can additionally or alternatively be used with other types offeature/characteristic detection techniques to confirm or ignoresuggested commercial transitions. Other example types offeature/characteristic detection techniques are described below inconnection with FIG. 10 .

Turning to FIG. 1 , a digital television broadcast environment 100 isshown depicting a manner in which digital television programs andcommercial advertisements are distributed to viewers. In FIG. 1 , anetwork television broadcaster 102 is shown receiving a televisionprogram 104 from a media content provider 106 and receiving a commercialadvertisement 108 from an advertiser 110. In the illustrated example,the network television broadcaster 102 inserts or splices the commercialadvertisement 108 into the television program 104 to generate a digitaltelevision broadcast feed 112. The television broadcast feed 112 canthen be distributed or broadcasted by the network television broadcaster102 through one or more broadcasting mediums including over-the-air(OTA) digital television broadcast media 114, cable distribution media116, and/or satellite distribution media 118. Although not shown, otherdistribution media may include Internet-based distribution (e.g.,internet-protocol television (IPTV)), wireless mobile networkdistribution, video on demand (VOD), Internet streaming (in time-shiftedor live manner), etc. The example techniques described herein canadditionally or alternatively be used in connection with such othertypes of distribution media.

The example commercial detection methods, apparatus, and articles ofmanufacture described herein can be used in households (e.g., ahousehold 120) or in media monitoring facilities (e.g., a mediamonitoring facility 122). For example, the household 120 may be a panelmember household in which media exposure monitoring is performed. Apanel member household is a household including one or more person(s)that participate in an audience measurement program. The household 120may be provided with a television/set-top-box monitoring device (e.g., amonitoring device including an example apparatus 1000 of FIG. 10 ) inwhich the example methods, apparatus, and articles of manufacturedescribed herein can be implemented to detect occurrences of commercialadvertisements during viewing sessions of digital television. The mediamonitoring facility 122 may be provided with a plurality of monitoringdevices (e.g., devices including the example apparatus 1000 of FIG. 10 )to monitor contents of television transmissions. The example methods,apparatus, and articles of manufacture described herein can also beimplemented in such monitoring devices so that the media monitoringfacility 122 can detect commercials in digital television transmissions.

In some example implementations, commercial advertisement insertion mayadditionally or alternatively be done by the media content provider 106.For example, for a nationally syndicated television show, the mediacontent provider 106 may receive nation-wide commercial advertisementsintended to appear nationally along with the syndicated television show.In such instances, the media content provider 106 may splice or insertthe commercial advertisements into the stream of the television program104 before distributing the television program to the network televisionbroadcaster 102 (and other broadcasters) for broadcast transmission.Further to such an example implementation, the network televisionbroadcaster 102 may have the option of replacing the nation-widecommercial advertisements with local commercial advertisements (e.g.,commercial advertisements for local businesses and/or for local targetaudiences) such that the commercial advertisement 108 may be a localcommercial advertisement intended to replace a nation-wide commercialadvertisement pre-inserted in the television program 104.

In the illustrated example of FIG. 1 , the television program 104 and/orthe commercial advertisement 108 may be provided to the networktelevision broadcaster 102 in analog or digital format. If provided indigital format, it may be provided in standard definition (SD)television format or high-definition (HD) television format. If providedin analog format or SD format, the network television broadcaster 102can perform conversion and/or up scaling processes to generate native HDtelevision transmission feeds. In this manner, the digital televisionbroadcast feed 112 can be broadcast to viewers in HD format.

Turning now to FIG. 2 , several frames of the television program 104provided by the media content provider 106 of FIG. 1 are shown. In theillustrated example, the television program 104 has an advertisementinsertion opportunity space 202 shown as one or more blank frames atwhich a commercial advertisement (e.g., the commercial advertisement 108of FIG. 1 ) may be inserted by the network television broadcaster 102.As discussed above, commercial advertisement insertion opportunities inthe television program 104 may be in the form of blank frames (as shownin FIG. 2 ) or in the form of other commercial advertisementspre-inserted by the media content provider 106 and replaceable by thenetwork television broadcaster 102. For example, the advertisementinsertion opportunity space 202 may include only blank frame(s), or itmay include one or more blank frame(s) followed by a pre-insertedadvertisement and/or promotional announcement to be potentiallyreplaced, which is followed by another one or more blank frame(s).

In the illustrated example, the television program 104 is shown in awidescreen profile format having a 16:9 aspect ratio. The first twoframes (frame 0 and frame 1) form a first program segment 204 and aframe N forms a second program segment 206. In the illustrated examplesdescribed herein, commercial advertisements are inserted into televisionprograms between program segments of the television programs. Forinstance, FIG. 2 shows that the advertisement insertion opportunityspace 202 appears between the first program segment 204 and the secondprogram segment 206 so that a commercial advertisement (e.g., thecommercial advertisement 108) can be inserted between the first andsecond program segments 204 and 206.

FIG. 3 depicts the commercial advertisement 108 provided by theadvertiser 110 of FIG. 1 and a box formatting process performed on thecommercial advertisement 108. In the illustrated example of FIG. 3 , theaspect ratio of the commercial advertisement 108 is different from thatof the television program 104 of FIGS. 1 and 2 . In particular, thecommercial advertisement 108 has an aspect ratio of 4:3 (full-screenprofile), while the television program 104 has an aspect ratio of 16:9(widescreen profile).

To enable insertion of the commercial advertisement 108 into thetelevision program 104 while preserving the aspect ratio of thecommercial advertisement 108, the commercial advertisement 108 is boxformatted as shown in FIG. 3 to form a pillarboxed commercialadvertisement 304. The type of box formatting used to facilitateinserting the 4:3 aspect ratio content of the commercial advertisement108 into 16:9 aspect ratio frames is a pillarbox formatting. As shown,pillarbox formatting pads or fills left and right sides of a 16:9 videoframe bordering the left and right sides of the advertisement 108 withscreen filler areas 302 that are displayed concurrently with thecommercial advertisement 108 on a 16:9 aspect ratio television screen.In the illustrated examples described herein, screen filler areas suchas the screen filler areas 302 are non-useable display areas ofdisplayed video frames as discussed above, while a useable display areaof a video frame is that portion of the video frame displayingcommercial advertisement content or television program content. In theillustrated example of FIG. 3 , the useable display area is that portionof the pillarboxed commercial advertisement 304 that displays thecommercial advertisement 108.

In some example implementations, the screen filler areas 302 can appearas black bars, gray bars or areas filled with any other solid colorand/or pattern. In other example implementations, the screen fillerareas 302 can be used to display television network logos or otherreadable or informative information, which may be displayed as staticimages or motion images. The example profile change detection techniquesdescribed herein can detect screen filler areas (e.g., the screen fillerareas 302) of a screen using edge detection techniques associated withimage recognition processes. Regardless of whether the screen fillerareas 302 of FIG. 3 are filled with solid colors, static images, ormotion images, bordering edges 306 between the commercial advertisement108 (a useable display area) and the screen filler areas 302(non-useable display areas) form respective, distinct edges between theseparate display areas that are detectable using edge detectionprocesses. In this manner, the profile change detection techniquesdescribed herein can determine when a profile change has occurred duringa transition from one frame to another as discussed below in connectionwith FIG. 4 . Additionally or alternatively, other imagerecognition/machine vision techniques can be used such as, for example,blob detection, color saturation detection, patterndetection/recognition, etc.

FIG. 4 depicts an example spliced television program feed 400 includingthe television program 104 (FIGS. 1 and 2 ) and the pillarboxedcommercial advertisement 304 of FIG. 3 . In the illustrated example ofFIG. 4 , when the pillarboxed commercial advertisement 304 is insertedinto the commercial insertion opportunity space 202 of FIG. 2 , aprofile change occurs during the transition between the first programsegment 204 and the presentation of the pillarboxed commercialadvertisement 304. That is, the frames of the first program segment 204contain useable display areas that fill the entire portion of a 16:9aspect ratio screen, while the pillarboxed commercial advertisement 304contains the screen filler areas 302 (FIG. 3 ) bordering the 4:3 aspectratio commercial advertisement 108. To detect the transition to thecommercial advertisement 104, an edge detection process can be employedto monitor occurrences of edges in the regions of the 16:9 aspect ratioframes at which the edges 306 (FIG. 3 ) are expected to appear duringtransitions between a television program and a commercial advertisement.

FIG. 5 depicts another example spliced television program feed 500exhibiting a different type of profile format change between televisionprogram frames and commercial advertisement frames. In particular, theexample original television program frames 502 of FIG. 5 are producedusing a 1.85:1 anamorphic widescreen aspect ratio, and the contents ofthe example commercial advertisement 504 fill 16:9 widescreen frames intheir entirety. Unlike the television program 104 of FIGS. 1, 2, and 4which has original frames that fill entire 16:9 aspect ratio videoframes, the original television program frames 502 of FIG. 5 must be boxformatted using letterbox formatting to maintain their original aspectratios but still be displayable on 16:9 widescreen format televisionscreens. However, the commercial advertisement 504 need not be boxformatted for display on 16:9 widescreen format television screensbecause it is produced using 16:9 aspect ratio video frames.

The letterbox formatting for the original television program videoframes 502 produces non-useable display areas 506 (e.g., screen fillerareas) bordering top and bottom edges of the frames 502. The edges 508created between the non-useable display areas 506 and the frames 502 canbe detected using edge detection processes to facilitate detectingtransitions to/from commercial advertisements. In particular, theexample methods, apparatus, and articles of manufacture described hereincan monitor the regions in which the edges 508 are expected to appear.When the edges 508 are detected as present, a transition to a commercialadvertisement is not suspected as having occurred. However, when theedges 508 are no longer detected, a profile format change is detected,suggesting that a transition to a commercial has occurred. For example,in the illustrated example of FIG. 5 , the edges 508 appear duringpresentation of the television program frames 502, but the edges 508disappear when the 16:9 aspect ratio commercial advertisement 504 isdisplayed.

FIG. 6 depicts another example digital television broadcast feed 600having a different type of spliced program and boxed advertisement thatcan be generated by the network television broadcaster 102 or the mediacontent provider 106 of FIG. 1 . In the illustrated example of FIG. 6 ,television program frames 602 are produced using 16:9 aspect ratio videoframes and an advertisement 604 is box formatted using a windowbox. Theexample methods, apparatus, and articles of manufacture for detectingprofile changes can also be used with the type of profile change shownin FIG. 6 to identify transitions between television program content andcommercial advertisement content or between different commercialadvertisements. In particular, edge detection processes can be used tomonitor any region of video frames where it can be expected that edges606 would appear when displaying a commercial advertisement as a resultof a screen filler area 608 associated with the windowbox formatting ofthe advertisement 604.

Although certain types of profile changes are depicted in FIGS. 4-6 ,the example methods, apparatus, and articles of manufacture describedherein to detect profile changes can be used in connection with othertypes of profile changes. For example, a television program may beletterbox formatted (FIG. 5 ) and spliced-in commercial advertisementscan be windowbox formatted (FIG. 6 ). In addition, transitions betweendifferent commercial advertisements can be detected based on profilechanges between different commercial advertisements. Also, while theabove describes detecting transitions from television program frames tocommercial advertisement frames, the example methods, apparatus, andarticles of manufacture described herein can similarly be used to detecttransitions from commercial advertisement frames to television programframes to identify when commercial advertisements have ended and when atelevision program has resumed.

FIG. 7 depicts video and audio portions of an example digital televisionbroadcast feed 700 having a television program segment 702 spliced witha commercial advertisement 704 generated by the network televisionbroadcaster 102, a distributor, and/or the media content provider 106 ofFIG. 1 . In the illustrated example of FIG. 7 , audio frames 706correspond to a first scene 708 of the television program 702 and audioframes 710 correspond to a second scene 712. The first scene 708 isseparated from the second scene 712 using one or more inter-scene blankframes 714 having one or more corresponding inter-scene audio frames716. Also in the illustrated example of FIG. 7 , the television programsegment 702 is separated from the advertisement 704 by one or moreinter-segment blank frames 718 having corresponding inter-segment blankaudio frames 720.

In the illustrated example, the inter-scene audio frames 716 can have anear-silence or low-volume audio tone characteristic providing audiblecontinuity between the scenes 708 and 712 to queue audience members of ascene change. Such audio characteristics of the inter-scene audio frames716 exhibit a sufficiently high level of loudness or non-randomness, andthe example techniques described herein interpret such loudness ornon-randomness to determine that the inter-scene audio frames 716 do nothint at or demarcate a commercial transition.

Unlike the inter-scene audio frames 716, the inter-segment blank audioframes 720 separating a program segment from an advertisement (orseparating two advertisements) exhibit audio characteristics havingeither a sufficiently low level of loudness or a relatively low level ofloudness in combination with a higher randomness factor than theinter-scene audio frames 716 to enable identifying a commercialtransition. A non-random or relatively low random characteristic ofinter-scene audio frames 716 is shown by way of example in FIG. 8 , anda high randomness characteristic of the inter-segment blank audio frames720 is shown by way of example in FIG. 9 .

The example methods, apparatus, and articles of manufacture describedherein can monitor levels of randomness of blank audio frames toidentify whether the blank audio frames correspond to inter-scene blankframes reflecting a scene change in a program such that subsequentvideo/audio frames are part of a television program or whether the blankaudio frames correspond to inter-segment blank frames indicating atransition between program content and an advertisement (or vice versa).When a sufficiently high level of randomness is detected in combinationwith relatively quiet audio, a commercial advertisement transition haslikely occurred.

In some example implementations, a random audio detection process isperformed only if audio during transition audio frames (e.g., theinter-scene blank frame(s) 714 or the inter-segment blank frame(s) 718)is quiet audio but not sufficiently quiet to confirm that the transitionaudio frames are of the type (e.g., the inter-segment blank frame(s)718) demarcating a commercial transition. For example, the techniquesdescribed herein can use a first audio level threshold to determinewhether audio is sufficiently quiet to indicate a commercial transitionwithout using a random audio analysis. A second audio level threshold(that is relatively higher than the first audio quietness threshold) canbe used to determine whether audio is sufficiently quiet to indicate acommercial transition if corroborated by also being sufficiently randomaudio.

The techniques described herein can use the first audio level thresholdto detect very quiet audio that is typically exhibited in inter-segmentblank frame(s) 718 of pure HDTV audio signals that were not convertedfrom original analog television signals. The second audio levelthreshold is higher than the first audio threshold level and can be usedto detect relatively quiet audio with higher levels of noise that istypically exhibited in inter-segment blank frame(s) 718 of HDTV audiosignals that were converted from original analog television audio.

In some example implementations, a root mean square operation can beused to identify audio levels in audio frames when monitoring for quietaudio portions. For example, a continuous digitized audio stream can beseparated into slices that are approximately equivalent to one videoframe such as, for example, one AC-3 frame of audio (0.032 seconds) orany other audio portion size.

For pure HDTV broadcasts (that were not converted from an analogsource), the RMS value of silence is near zero. However, not alltelevision broadcast stations provide such pure HDTV broadcasts. Forexample, some stations may convert analog signals to HDTV signals. Suchdigitization processes introduce low level noise (e.g., a hiss). Thus,using the audio monitoring techniques described herein, an audio framehaving a RMS level below a first audio level threshold can be regardedas being a possible commercial transition without needing to perform arandom audio analysis. For any audio frame having a RMS value above thefirst audio level threshold but below a second audio level threshold, arandom audio analysis may be performed to confirm the likelihood thatsuch relatively quiet audio is a commercial transition rather than aninter-scene blank frame 714 with a tone or other sound occurring betweenscene changes.

FIG. 8 depicts an example time-based inter-scene audio waveform 800 ofnon-random audio that can accompany the inter-scene blank frames 714 ofFIG. 7 within the television program segment 702 of the digitaltelevision broadcast feed 700. FIG. 9 depicts another example time-basedaudio waveform 900, which has random audio that can accompany theinter-segment blank audio frames 720 of FIG. 7 . As discussed above, theexample methods, apparatus, and articles of manufacture described hereincan distinguish between inter-scene audio frames and inter-segment audioframes by detecting the amounts of randomness in the audio of thoseframes. In some examples, this degree of randomness is determined bycounting the quantity of unique time-based distances between peaks andtroughs of the respective time-based audio waveforms and generating arandom-factor ratio (e.g., a randomness factor) by dividing the quantityof unique time-based distances by the number of total peak-to-peakdistances and trough-to-trough distances. In the examples describedherein, a peak is an audio sample having a local relative maximumamplitude value and a trough is an audio sample having a local relativeminimum amplitude value.

To illustrate this approach of generating a randomness factor or arandom-factor ratio of one or more audio frames, if 200 peaks (e.g.,peaks having similar amplitude values) and 200 troughs (e.g., troughshaving similar amplitude values) are identified and all of thepeak-to-peak and trough-to-trough distances are either 17 or 18 audiosamples apart, then there are two unique distances (i.e., 17 and 18) outof 400 total peaks and troughs. Thus, the random-factor ratio is 2:400or 0.005 (i.e., the randomness factor). Such a random-factor ratio isindicative of a very non-random sound. In the illustrated example, sucha random-factor ratio is indicative of a practically constant tone. Ifthe sound were a highly-random “hiss,” the corresponding audio frameswould have a relatively higher quantity of peak-to-peak andtrough-to-trough unique distances (e.g., 250 unique distances, for arandomness factor of 250:400 or 0.625). In some example implementations,to perform faster integer-based computations rather than slowerfloating-point computations, random-factor ratios can be multiplied by1,000. Although the illustrated example, is described in connection withusing time-based distances between amplitude peaks in combination withtime-based distances between amplitude troughs, in other exampleimplementations, time-based distances can be collected and used based ononly amplitude peaks or based on only amplitude troughs.

In some implementations, other types of techniques may be used todetermine randomness of audio signals. Other example randomnessdetermination techniques include stochastic modeling, statistical tests,transforms, and/or complexity tests.

In the illustrated examples described herein, a randomness threshold canbe used to determine whether audio is sufficiently random to indicate orsuggest a commercial advertisement transition. The randomness thresholdmay be a predetermined value or may be a learned value that changes overtime based on historical data, prediction algorithms, and/or manualadjustment. Such a randomness threshold could be in the form of arandom-factor ratio value. Although an example randomness detectiontechnique has been described as being implemented by countingpeak-to-peak distances and trough-to-trough distances, in other exampleimplementations other types of techniques can be used such ascryptography or other signal analysis techniques.

In FIG. 8 , time-based distances or durations (t₀), (t₁), and (t₂)between select peaks 802 having similar amplitudes are substantiallyequal to one another and, thus, are counted as a single uniquepeak-to-peak distance. Time-based distances or durations (t₃), (t₄), and(t₅) between select troughs 804 of similar amplitudes are alsosubstantially equal to one another and, thus, are counted as a singleunique trough-to-trough distance. If the peak-to-peak distances and thetrough-to-trough distances are all substantially equal or similar, thenthey are considered a single unique distance, otherwise they areconsidered two separate unique distances.

During a peak-to-peak or trough-to-trough duration measurement process,the durations between corresponding peaks or between correspondingtroughs need not be exactly equal to one another to constitute a singleunique distance. Instead, the peak-to-peak or trough-to-trough durationscan be sufficiently the same within a particular tolerance threshold toconstitute a single unique distance.

In contrast to FIG. 8 , peaks and troughs of the time-basedinter-segment audio waveform 900 of FIG. 9 exhibit random durationstherebetween such that the randomness factor of the inter-segment audiowaveform 900 is relatively high. For example, durations (t₆), (t₇), and(t₈) of select troughs 902 having similar amplitudes are not similar toone another and, thus, are counted as three separate and uniquedistances. A similar process can be used to analyze trough-to-troughdistances. This dissimilarity in peak-to-peak durations ischaracteristic of the relatively high randomness of the inter-segmentaudio waveform 900. Such relatively high randomness is characteristic ofinter-segment blank audio frames (e.g., the inter-segment blank audioframes 718 of FIG. 7 ), which can be indicative or suggestive oftransitions between television program content and advertisementcommercials or between separate advertisement commercials.

FIG. 10 depicts an example apparatus 1000 that can be used to detectcommercial advertisements (e.g., the commercial advertisements 108, 504,604, and 704 of FIGS. 1 and 3-7 ) in digital television feeds (e.g., thedigital television feeds 104, 112, 400, 500, 600, and 700 of FIGS. 1, 2,and 4-7 ). In the illustrated example, the example apparatus 1000includes a frame detector 1002, a video frame re-constructor 1004, anaudio frame re-constructor 1006, a video frame buffer 1008, an imagefeatures detector 1010, an audio frame buffer 1012, an audio featuresdetector 1014, a commercial hint generator 1016, a weighting generator1018, and an advertisement detector 1020. The example apparatus 1000 maybe implemented using any desired combination of hardware, firmware,and/or software. For example, one or more integrated circuits, discretesemiconductor components, and/or passive electronic components may beused. Thus, for example, any of the frame detector 1002, the video framere-constructor 1004, the audio frame re-constructor 1006, the videoframe buffer 1008, the image features detector 1010, the audio framebuffer 1012, the audio features detector 1014, the commercial hintgenerator 1016, the weighting generator 1018, and/or the advertisementdetector 1020, or parts thereof, could be implemented using one or morecircuit(s), programmable processor(s), application specific integratedcircuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)), fieldprogrammable logic device(s) (FPLD(s)), etc.

Some or all of the frame detector 1002, the video frame re-constructor1004, the audio frame re-constructor 1006, the video frame buffer 1008,the image features detector 1010, the audio frame buffer 1012, the audiofeatures detector 1014, the commercial hint generator 1016, theweighting generator 1018, and/or the advertisement detector 1020, orparts thereof, may be implemented using instructions, code, and/or othersoftware and/or firmware, etc. stored on a tangible machine accessiblemedium and executable by, for example, a processor system (e.g., theexample processor system 1510 of FIG. 15 ). When any of the appendedapparatus claims are read to cover a purely software and/or firmwareimplementation, at least one of the frame detector 1002, the video framere-constructor 1004, the audio frame re-constructor 1006, the videoframe buffer 1008, the image features detector 1010, the audio framebuffer 1012, the audio features detector 1014, the commercial hintgenerator 1016, the weighting generator 1018, and/or the advertisementdetector 1020 is hereby expressly defined to include a tangible mediumsuch as a memory, a digital versatile disk (DVD), a compact disc (CD),etc. storing such software and/or firmware.

To receive and detect frames in a digital television feed 1022 (e.g.,the digital television feeds 112, 400, 500, 600, and 700 of FIGS. 1, 4,5, 6 , and 7), the example apparatus 1000 is provided with the framedetector 1002. To re-construct video frames of the digital televisionfeed 1022, the example apparatus 1000 is provided with the video framere-constructor 1004. To re-construct audio frames of the digitaltelevision feed 1022, the example apparatus 1000 is provided with theaudio frame re-constructor 1006. In some example implementations, theframe detector 1002, the video frame re-constructor 1004, and the audioframe re-constructor 1006 can be implemented as part of a video decoder1024.

To store video frames for analysis, the example apparatus 1000 isprovided with the video frame buffer 1008. For example, the video framebuffer 1008 may store video frames to perform image recognitionprocesses such as edge detection processes (or other imagerecognition/machine vision processes) to detect changes in profileformat as described above in connection with FIGS. 4-6 . To performimage recognition/machine vision processes such as edge detectionprocesses, the example apparatus 1000 is provided with the imagefeatures detector 1010. The example apparatus 1000 may be configured tocontrol the image features detector 1010 to analyze regions of framesthat may exhibit edges (e.g., the edges 306 (FIG. 3 ), the edges 508(FIG. 5 ), the edges 606 (FIG. 6 )) resulting from one or more type(s)of box formatting as described above in connection with FIGS. 3-6 .Although the illustrated examples for profile change detection aredescribed herein as using edge detection techniques, other imagerecognition/machine vision techniques could additionally oralternatively be used such as blob detection, color saturationdetection, pattern detection/recognition, etc.

To store audio frames for analysis, the example apparatus 1000 isprovided with the audio frame buffer 1012. For example, the audio framebuffer 1010 may store audio frames to perform random audio detectionprocesses as described above in connection with FIGS. 7-9 . To detectfeatures of audio from digital television feeds and perform random audiodetection processes, the example apparatus 1000 is provided with theaudio features detector 1014. The example apparatus 1000 may beconfigured to control the audio features detector 1014 to detect audioframes having audio amplitudes below a certain power level (e.g., belowa specified volume level indicative of near-silent or quiet audio) oraudio frames corresponding with blank video frames and analyze therandomness of such audio frames to determine whether such audio framesare inter-scene audio frames (e.g., the inter-scene audio frames 716 ofFIG. 7 ) or inter-segment audio frames (e.g., the inter-segment audioframes 720 of FIG. 7 ). As discussed above, the amount of randomness innear-silent or quiet audio frames can be indicative or suggestive of atransition to or from a commercial advertisement (e.g., the commercialadvertisement 704 of FIG. 7 ).

To generate hints indicative or suggestive of a possible transitionbetween a television program segment and a commercial advertisement orbetween separate commercial advertisements, the example apparatus 1000is provided with the commercial hint generator 1016. The commercial hintgenerator 1016 may be configured to generate a hint with a detectiontechnique identifier each time a possible commercial advertisementtransition is suggested by a particular detection technique. Forexample, hints generated based on detecting a change in profile format(as discussed above in connection with FIGS. 3-6 ) may be provided witha unique identifier corresponding to the profile format detectiontechnique, while hints generated based on detecting random audio inconnection with blank video frames (as discussed above in connectionwith FIGS. 7-9 ) may be provided with a different unique identifiercorresponding to the random audio detection technique.

To generate weighting values for different types of commercial hintsgenerated by the commercial hint generator 1016, the example apparatus1000 is provided with the weighting generator 1018. In the illustratedexample, the weighting generator 1018 is configured to generate weightvalues based on the amount of confidence that should be placed on eachtype of hint to determine whether a commercial advertisement transitionhas actually occurred in a television program feed. Such weightingvalues can be based on historical data indicative of accuracy levelsobserved for each type of hint. Such accuracy levels may berepresentative of the percentage of times that generation of aparticular type of hint was correctly indicative of an actual commercialadvertisement transition. Additionally or alternatively, such weightingvalues can be based on the robustness or repeatability of differenttypes of commercial transition detection techniques.

Weighted commercial hint values can be used in a voting-type process todetermine or confirm whether a commercial advertisement transitionactually occurred in a digital television feed. To implement thevoting-type process, the example apparatus 1000 is provided with anadvertisement detector 1020. In the illustrated example, theadvertisement detector 1020 receives all of the different types ofweighted commercial hint values generated for the same one or morevideo/audio frames of the digital television feed 1022. Theadvertisement detector 1020 then determines an aggregate weighted hintvalue of all the received weighted hint values and determines whether acommercial advertisement transition actually occurred based on whetherthe aggregate weighted hint value exceeds a weighted hint valuethreshold. The weighted hint value threshold may be predetermined or maychange based on various factors or manual input.

Although the profile change detection technique and the random audiodetection technique are described herein in detail, the commercial hintgenerator 1016 and the weighting generator 1018 can additionally oralternatively be used in connection with other types of commercialdetection techniques. Such other types of commercial detectiontechniques can include detecting changes in frame aspect ratios ofdigital television feeds, detecting blank frames, detecting changes inaudio formats (e.g., 5.1 audio, stereo audio, mono audio, etc.),detecting discontinuities in timing information (e.g., MPEGPresentationTimeStamp (PTS) codes) associated with digital encodingstandards such as MPEG-2 coding standards (Motion Picture Expert Group(MPEG)), detecting startings/stoppings of closed-captioning text,detecting commercial insertion opportunity codes (e.g., SCTE35 codes insatellite television transmissions), and detecting ancillary audioand/or video identification codes embedded into frames of televisionprograms and/or commercial advertisements.

Detecting changes in frame aspect ratios differs from the profile changedetection techniques described herein. Under the profile changesdescribed above in connection with FIGS. 3-6 , the displayable videoframe aspect ratio (e.g., what a television actually displays and aviewer actually sees displayed) of a digital television broadcast feeddoes not change when transitioning between a television program segmentand a commercial advertisement. Instead, to keep the displayable videoframe aspect ratio the same (e.g., a 16:9 aspect ratio) whentransitioning between commercial advertisements and television programsegments, box formatting techniques are used as described above. Incontrast, detecting changes in displayable video frame aspect ratiosinvolves detecting when a broadcaster has changed the aspect ratios ofthe displayable video frames. For example, a broadcaster may broadcastvideo frames of television program segments using a 16:9 aspect ratioand broadcast video frames of commercial advertisements using a 4:3aspect ratio. The 4:3 aspect ratio video frames would either appearstretched on a 16:9 widescreen television screen or a television (orset-top-box) would pillarbox the 4:3 video frames locally at the viewingsite and display the 4:3 aspect ratio video frames as pillarboxed frameson the 16:9 widescreen television screen.

The profile change detection techniques described herein can beadvantageously used when broadcasters broadcast digital televisionprograms and commercials without changing video frame aspect ratios andinstead decide to box format video frames, when necessary, to fit asingle aspect ratio (e.g., a 16:9 aspect ratio). Some broadcastersdecide to broadcast in this manner (instead of transmitting every videoframe in its native aspect ratio) to avoid frequent switching inbroadcast aspect ratios and, thus, avoid any type of televisionbroadcast, reception, decoding, or display error that could occur in theprocess.

Changes in audio formats can be indicative of transitions betweentelevision program segments and commercial advertisements. For example,an HD-quality digital television program may be broadcast with 5.1surround sound audio, while a commercial advertisement may be broadcastwith stereo or mono audio. These changes in audio formats within adigital television broadcast feed can be indicative or suggestive oftransitions between television program segments and commercialadvertisements.

Discontinuities in timing information associated with digital encodingstandards (e.g., the MPEG-2 encoding standard) can also be indicative oftransitions between television program segments and commercialadvertisements. For example, when a commercial advertisement is insertedbetween television program segments, the media encoding timinginformation (e.g., MPEG PTS codes) associated with the televisionprogram segments is disrupted by the media encoding time informationassociated with the inserted commercial advertisement. These disruptionsor discontinuities in media encoding timing information can beindicative or suggestive of transitions between television programsegments and commercial advertisements.

Ancillary audio and/or video identification codes can be embedded intoframes of television programs and/or commercial advertisements usingwatermarking techniques or any other code insertion techniques. Suchcodes or watermarks can be used to detect commercial advertisementtransitions by detecting specific codes/watermarks corresponding tocommercial advertisement content, changes from non-coded/non-watermarkedcontent to coded/watermarked content, and/or changes fromcoded/watermarked content to non-coded/non-watermarked content. Suchdetections of specific codes/watermarks or changes betweennon-coded/non-watermarked content and coded/watermarked content can beindicative of a transition to or from a commercial advertisement.

FIGS. 11-13 are flow diagrams representative of machine readableinstructions that can be executed to implement the methods and apparatusdescribed herein. The example processes of FIGS. 11-13 may beimplemented using machine readable instructions that, when executed,cause a device (e.g., a programmable controller or other programmablemachine or integrated circuit) to perform the operations shown in FIGS.11-13 . For instance, the example processes of FIGS. 11-13 may beperformed using a processor, a controller, and/or any other suitableprocessing device. For example, the example process of FIGS. 11-13 maybe implemented using coded instructions stored on a tangible machinereadable medium such as a flash memory, a read-only memory (ROM), and/ora random-access memory (RAM).

As used herein, the term tangible computer readable medium is expresslydefined to include any type of computer readable storage and to excludepropagating signals. Additionally or alternatively, the exampleprocesses of FIGS. 11-13 may be implemented using coded instructions(e.g., computer readable instructions) stored on a non-transitorycomputer readable medium such as a flash memory, a read-only memory(ROM), a random-access memory (RAM), a cache, or any other storage mediain which information is stored for any duration (e.g., for extended timeperiods, permanently, brief instances, for temporarily buffering, and/orfor caching of the information). As used herein, the term non-transitorycomputer readable medium is expressly defined to include any type ofcomputer readable medium and to exclude propagating signals.

Alternatively, the example processes of FIGS. 11-13 may be implementedusing any combination(s) of application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)), field programmablelogic device(s) (FPLD(s)), discrete logic, hardware, firmware, etc.Also, the example processes of FIGS. 11-13 may be implemented as anycombination(s) of any of the foregoing techniques, for example, anycombination of firmware, software, discrete logic and/or hardware.

Although the example processes of FIGS. 11-13 are described withreference to the flow diagrams of FIGS. 11-13 , other methods ofimplementing the processes of FIGS. 11-13 may be employed. For example,the order of execution of the blocks may be changed, and/or some of theblocks described may be changed, eliminated, sub-divided, or combined.Additionally, one or both of the example processes of FIGS. 11-13 may beperformed sequentially and/or in parallel by, for example, separateprocessing threads, processors, devices, discrete logic, circuits, etc.

Turning now to FIG. 11 , an illustrated flow diagram is representativeof machine readable instructions that can be executed to detectcommercial advertisements in digital television feeds based onmonitoring box-format areas in video frames. The example process of FIG.11 can be used to detect profile changes as discussed above inconnection with FIGS. 3-6 . Initially, frame detector 1002 (FIG. 10 )receives a television feed (e.g., the digital television feed 1022 ofFIG. 10 ) (block 1102). The video frame re-constructor 1004 (FIG. 10 )constructs individual video frames (block 1104), and the video framebuffer 1008 (FIG. 10 ) buffers the re-constructed video frames (block1106).

The image features detector 1010 (FIG. 10 ) monitors box-format areas(block 1108) of the buffered video frames. The monitoring can beperformed to detect the appearance or disappearance of screen fillerareas (e.g., the screen filler areas 302 of FIG. 3 , the non-useabledisplay areas 506 of FIG. 5 , or the screen filler area 608 of FIG. 6 )between frame transitions. For example, the image features detector 1010can perform edge detection processes in regions in which edges (e.g.,the edges 306 (FIG. 3 ), 508 (FIG. 5 ), and 606 (FIG. 6 )) associatedwith box formatting would be expected to appear. The image featuresdetector 1010 can use such edge detection processes to detect a changein the display of box-format edges such as a frame-to-frame transitionthat causes the box-format edges to appear or disappear. For example,referring to FIG. 4 , a transition from the first program segment 204 tothe pillarboxed commercial advertisement 304 causes the edges 306 (FIG.3 ) to appear. Referring to FIG. 5 , a transition from a televisionprogram segment to a commercial advertisement 504 causes the edges 508to disappear due to the letterboxed television program frames and thenon-boxed commercial advertisement 504. Thus, in FIG. 4 , the appearanceof box-format edges is suggestive of a commercial advertisementtransition, while in FIG. 5 , the disappearance of box-format edges issuggestive of a commercial advertisement transition. In alternativeexample implementations, other image recognition/machine visiontechniques (e.g., blob detection, color saturation detection, patterndetection/recognition, etc.) can additionally or alternatively be usedto detect the appearance or disappearance of screen filler areas betweenframe transitions.

The image features detector 1010 determines whether it has detected aprofile change (e.g., a box-formatting change) in the buffered videoframes (block 1110). For example, as discussed above, the image featuresdetector 1010 can detect a profile change by using edge detectiontechniques to detect changes in the display of box-format edges. Inother example implementations, other types of image recognitiontechniques could be used including blob detection, color saturationdetection, etc.

If the image features detector 1010 detects a profile change in thebuffered video frames (block 1110), the commercial hint generator 1016(FIG. 10 ) generates a hint (block 1112). As discussed above, the hintindicates that a commercial advertisement transition may have occurred.The hint can be labeled, flagged, or tagged with an identifierindicative of the detection technique (e.g., profile change detection)that caused the hint to be generated. The weighting generator 1018 (FIG.10 ) generates a weighting value for the hint (block 1114). As discussedabove, the weighting value can be generated based on the amount ofconfidence that should be placed on the type of hint to determinewhether a commercial advertisement transition has actually occurred in atelevision program feed.

The advertisement detector 1020 (FIG. 10 ) then analyzes the weightedhint value (block 1116). For example, as discussed above, theadvertisement detector 1020 can receive multiple weighted hint values,each corresponding to a different technique used to detect a commercialadvertisement transition at approximately the same time during a digitaltelevision program feed. In this manner, the advertisement detector 1020can determine based on all the weighted hint values whether a commercialadvertisement transition actually occurred. An example process that canbe used to implement the weighted hint value analysis of block 1116 isdescribed below in connection with FIG. 14 .

If the advertisement detector 1020 confirms that a commercialadvertisement transition has occurred (block 1118), the advertisementdetector 1020 indicates a transition point of the digital televisionfeed 1022 (FIG. 10 ) that corresponds to the one or more generated hintsas a commercial advertisement transition (block 1120) (e.g., atransition from a television program segment to a commercialadvertisement (or vice versa) or between two separate commercialadvertisements). For example, the advertisement detector 1020 mayindicate the transition point by forwarding a message indicative of thetransition to a commercial identification system (not shown) to triggerthe commercial identification system to identify a commercialadvertisement presented following the transition point. Additionally oralternatively, the advertisement detector 1020 may indicate thetransition point by labeling, flagging, or tagging the transition pointin the digital television feed 1022 (FIG. 10 ) as a commercialadvertisement transition.

If the advertisement detector 1020 determines that a commercialadvertisement transition has not occurred (block 1118), theadvertisement detector 1020 ignores the evaluated portion of the digitaltelevision feed 1022 that corresponds to the one or more generated hints(block 1122). After the advertisement detector 1020 ignores theevaluated portion of the digital television feed 1022 (block 1122) orafter the advertisement detector 1020 indicates a transition point ofthe digital television feed 1022 as a commercial advertisementtransition (block 1120) or if a profile change is not detected (block1110), the example apparatus 1000 determines whether to continuemonitoring (block 1124). If the example apparatus 1000 determines thatit should continue monitoring (block 1124), control returns to block1108. Otherwise, the example process of FIG. 11 is ended.

FIG. 12 is a flow diagram representative of machine readableinstructions that can be executed to detect commercial advertisements indigital television feeds based on monitoring audio frames. The exampleprocess of FIG. 12 can be used to detect levels of randomness in quiet,silent, or near-silent audio frames as discussed above in connectionwith FIGS. 7-9 . Initially, frame detector 1002 (FIG. 10 ) receives atelevision feed (e.g., the digital television feed 1022 of FIG. 10 )(block 1202). The audio frame re-constructor 1006 (FIG. 10 ) constructsindividual audio frames (block 1204), and the audio frame buffer 1012(FIG. 10 ) buffers the re-constructed audio frames (block 1206).

The audio features detector 1014 monitors the buffered audio frames(block 1208). For example, the audio features detector 1014 can monitorfor silent, near-silent, or quiet audio, which can be suggestive ofcommercial advertisement transitions as discussed above in connectionwith FIGS. 7-9 . In the illustrative examples described herein, theaudio features detector 1014 monitors the buffered audio frames based onfirst and second audio level thresholds discussed above in connectionwith FIG. 7 in which the first threshold indicates a lower audio levelthan the second threshold.

If the audio features detector 1014 detects silent, near-silent, orquiet audio below the first audio level threshold (block 1210), controladvances to block 1218 at which a commercial transition hint isgenerated. However, if the audio features detector 1014 does not detectsilent, near-silent, or quiet audio below a first audio level threshold(block 1210), the audio features detector 1014 compares the same portionof audio to the second audio level threshold (block 1212). If the audiofeatures detector 1014 detects silent, near-silent, or quiet audio belowthe second audio level threshold (block 1212), the audio featuresdetector 1014 performs a random audio analysis (block 1214) on the audioframes. An example process that can be used to perform the random audioanalysis of block 1214 is discussed below in connection with FIG. 13 .

If the audio features detector 1014 determines that the audio of theanalyzed audio frames has a sufficiently high level of randomness (e.g.,randomness above a random threshold level) (block 1216) or if the audiofeatures detector 1014 detects silent, near-silent, or quiet audio belowthe first audio level threshold (block 1210), the commercial hintgenerator 1016 (FIG. 10 ) generates a hint (block 1218). As discussedabove, the hint is suggestive that a commercial advertisement transitionmay have occurred. The hint is tagged with an identifier indicative ofthe detection technique that caused the hint to be generated. Forexample, the detection technique tag may indicate that the hintcorresponds to detecting a sufficiently low audio level (e.g., block1210) or detecting sufficiently random audio (e.g., block 1216). Theweighting generator 1018 (FIG. 10 ) generates a weighting value for thehint (block 1220). As discussed above, the weighting value can begenerated based on the amount of confidence that should be placed on thetype of hint to determine whether a commercial advertisement transitionhas actually occurred in a television program feed.

The advertisement detector 1020 (FIG. 10 ) then analyzes the weightedhint value (block 1222). For example, as discussed above, theadvertisement detector 1020 can receive multiple weighted hint values,each corresponding to a different technique used to detect a commercialadvertisement transition at approximately the same time during a digitaltelevision program feed. In this manner, the advertisement detector 1020can determine based on all the weighted hint values whether a commercialadvertisement transition actually occurred. An example process that canbe used to implement the weighted hint value analysis of block 1222 isdescribed below in connection with FIG. 14 .

If the advertisement detector 1020 confirms that a commercialadvertisement transition has occurred (block 1224), the advertisementdetector 1020 indicates a transition point of the digital televisionfeed 1022 (FIG. 10 ) that corresponds to the one or more generated hintsas a commercial advertisement transition (block 1226) (e.g., atransition from a television program segment to a commercialadvertisement (or vice versa) or between two separate commercialadvertisements). For example, the advertisement detector 1020 mayindicate the transition point by forwarding a message indicative of thetransition point to a commercial identification system (not shown) totrigger the commercial identification system to identify a commercialadvertisement presented following the transition point. Additionally oralternatively, the advertisement detector 1020 may indicate thetransition point by labeling, flagging, or tagging the transition pointin the digital television feed 1022 (FIG. 10 ) as a commercialadvertisement transition.

If the advertisement detector 1020 determines that a commercialadvertisement transition has not occurred (block 1224), theadvertisement detector 1020 ignores the evaluated portion of the digitaltelevision feed 1022 that corresponds to the one or more generated hints(block 1228). After the advertisement detector 1020 ignores theevaluated portion of the digital television feed 1022 (block 1228) orafter the advertisement detector 1020 indicates a transition point inthe digital television feed 1022 as having a commercial advertisementtransition (block 1226) or if random audio is not detected (block 1216)or if silent, near-silent, or quiet audio below the second audio levelthreshold is not detected (block 1212), the example apparatus 1000determines whether to continue monitoring (block 1230). If the exampleapparatus 1000 determines that it should continue monitoring (block1230), control returns to block 1208. Otherwise, the example process ofFIG. 12 is ended.

Although the example processes of FIGS. 11 and 12 are described usingseparate flow diagrams, the example processes could be implemented onthe same commercial detection device and performed in parallel such thatboth commercial transition detection techniques can be used to generaterespective types of hints indicative or suggestive of commercialadvertisement transitions. In this manner, the advertisement detector1020 (FIG. 10 ) can determine whether a commercial advertisementtransition actually occurred based on both types of weighted hintvalues. Weighted hint values from other types of commercial transitiondetection techniques discussed above in connection with FIG. 10 mayadditionally or alternatively be used by the advertisement detector 1020to perform weighted hint analyses.

FIG. 13 is a flow diagram representative of machine readableinstructions that can be executed to perform random audio analyses inconnection with the example process of FIG. 12 . Initially, the audiofeatures detector 1014 identifies the amplitude peaks (e.g., the peaks802 of FIG. 8 ) (block 1302) and the amplitude troughs (e.g., thetroughs 804 of FIG. 8 ) (block 1304) in one or more audio frames (e.g.,one or more audio frames detected at block 1212 of FIG. 12 as havingnear-silent or quiet audio).

The audio features detector 1014 measures the time-based distances (ordurations) between neighboring consecutive peaks and between neighboringconsecutive troughs (block 1306) as discussed above in connection withFIGS. 8 and 9 . The audio features detector 1014 then tallies thequantity of unique distances between peaks and troughs (block 1308) andgenerates a random-factor ratio (block 1310). For example, the audiofeatures detector 1014 can generate the random-factor ratio as discussedabove in connection with FIGS. 7-9 by dividing the quantity of uniquedistances by a total quantity of all of the peaks and troughs identifiedat blocks 1302 and 1304.

The audio features detector 1014 then determines whether therandom-factor ratio indicates a sufficiently random audio signal toqualify as a commercial transition (block 1312). For example, theexample apparatus 1000 can be provided (e.g., pre-programmed) with arandom level threshold indicating an amount of randomness (based on arandom-factor ratio) that should be found in audio to confirm the audioas being sufficiently random. In the illustrated examples describedherein, such sufficient randomness is indicative or suggestive of acommercial advertisement transition.

If the audio features detector 1014 determines that the audio issufficiently random to quality as a commercial transition (block 1312),the audio features detector 1014 indicates the one or more audio framesas having random noise (e.g., label the one or more audio frames as acommercial transition) (block 1314), and the example process of FIG. 13returns control to a calling function or process such as the exampleprocess of FIG. 12 and ends. Otherwise, if the audio features detector1014 determines that the audio is not sufficiently random to qualify asa commercial transition (block 1312), the audio features detector 1014indicates the one or more audio frames as having non-random audio (block1316), and the example process of FIG. 13 returns control to a callingfunction or process such as the example process of FIG. 12 and ends.Although the flow diagram of FIG. 13 describes determining randomnessbased on distances between peaks and troughs, other types of techniquesmay be used to determine randomness of audio signals such as, forexample, stochastic modeling, statistical tests, transforms, and/orcomplexity tests.

FIG. 14 is a flow diagram representative of machine readableinstructions that can be executed to perform weighted hint analyses inconnection with the example processes of FIGS. 11 and 12 to confirmcommercial advertisement transitions in digital television feeds.Initially, the advertisement detector 1020 (FIG. 10 ) receives all ofthe generated hint values for the same television feed portion (e.g.,all hints generated for the transition between the first program segment204 and the pillarboxed commercial advertisement 304 of FIG. 4 or allhints generated for the inter-segment blank frames 718 of FIG. 7 )(block 1402). The advertisement detector 1020 aggregates all of theweighted hint values (block 1404) and determines whether the aggregateweighted hint score exceeds a weighted hint threshold (block 1406). Theweighted hint threshold value may be a pre-determined value selected asan indicator of the amount of hint score confidence that needs to existto confirm that a commercial advertisement transition has occurred. Asexplained above, the weighted hint threshold may vary over time.

If the advertisement detector 1020 determines that the aggregateweighted hint score exceeds the weighted hint threshold (block 1406),the advertisement detector 1020 generates a commercial advertisementtransition confirmation flag (block 1408). Otherwise, if theadvertisement detector 1020 determines that the aggregate weighted hintscore does not exceed the weighted hint threshold (block 1406), theadvertisement detector 1020 generates an ignore flag (block 1410). Afterthe advertisement detector 1020 generates a commercial advertisementtransition confirmation flag at block 1408 or generates an ignore flagat block 1410, control returns to a calling function or process such asthe example process of FIG. 11 or the example process of FIG. 12 and theexample process of FIG. 14 ends.

FIG. 15 is a block diagram of an example processor system 1510 that maybe used to implement the example apparatus, methods, and systemsdescribed herein. For example, a processor system substantially similaror identical to the example processor system 1510 may be used toimplement the example apparatus 1000 of FIG. 10 .

As shown in FIG. 15 , the processor system 1510 includes a processor1512 that is coupled to an interconnection bus 1514. The processor 1512may be any suitable processor, processing unit, or microprocessor.Although not shown in FIG. 15 , the system 1510 may be a multi-processorsystem and, thus, may include one or more additional processors that areidentical or similar to the processor 1512 and that are communicativelycoupled to the interconnection bus 1514.

The processor 1512 of FIG. 15 is coupled to a chipset 1518, whichincludes a memory controller 1520 and an input/output (I/O) controller1522. A chipset provides I/O and memory management functions as well asa plurality of general purpose and/or special purpose registers, timers,etc. that are accessible or used by one or more processors coupled tothe chipset 1518. The memory controller 1520 performs functions thatenable the processor 1512 (or processors if there are multipleprocessors) to access a system memory 1524 and a mass storage memory1525.

In general, the system memory 1524 may include any desired type ofvolatile and/or non-volatile memory such as, for example, static randomaccess memory (SRAM), dynamic random access memory (DRAM), flash memory,read-only memory (ROM), etc. The mass storage memory 1525 may includeany desired type of mass storage device including hard disk drives,optical drives, tape storage devices, etc.

The I/O controller 1522 performs functions that enable the processor1512 to communicate with peripheral input/output (I/O) devices 1526 and1528 and a network interface 1530 via an I/O bus 1532. The I/O devices1526 and 1528 may be any desired type of I/O device such as, forexample, a keyboard, a video display or monitor, a mouse, etc. Thenetwork interface 1530 may be, for example, an Ethernet device, anasynchronous transfer mode (ATM) device, an 802.11 device, a digitalsubscriber line (DSL) modem, a cable modem, a cellular modem, etc. thatenables the processor system 1510 to communicate with another processorsystem.

While the memory controller 1520 and the I/O controller 1522 aredepicted in FIG. 15 as separate functional blocks within the chipset1518, the functions performed by these blocks may be integrated within asingle semiconductor circuit or may be implemented using two or moreseparate integrated circuits.

Although certain methods, apparatus, systems, and articles ofmanufacture have been described herein, the scope of coverage of thispatent is not limited thereto. To the contrary, this patent covers allmethods, apparatus, systems, and articles of manufacture fairly fallingwithin the scope of the appended claims either literally or under thedoctrine of equivalents.

What is claimed is:
 1. An apparatus comprising: at least one memory;instructions in the apparatus; and processor circuitry to execute theinstructions to: generate a first hint value based on a firstcharacteristic associated with a media presentation, the firstcharacteristic indicative of a commercial transition; generate a secondhint value based on a second characteristic associated with the mediapresentation, the second characteristic indicative of the commercialtransition; determine an aggregated weighted hint value based on thefirst hint value and the second hint value; and indicate a presence ofthe commercial transition associated with the media presentation basedon a determination that the aggregated weighted hint value satisfies athreshold.
 2. The apparatus of claim 1, wherein the threshold is a firstthreshold, the first characteristic is an amount of audio randomness inan inter-segment audio frame of the media presentation, and theprocessor circuitry is to: determine the amount of audio randomnessbeing based on a random-factor ratio; and generate the first hint valuebased on a comparison of the amount of audio randomness to a secondthreshold.
 3. The apparatus of claim 1, wherein the secondcharacteristic is a presence of at least one of a change inbox-formatting between consecutive video frames, an audio format change,an aspect ratio change, a timestamp discontinuity, a closed-captioningtext discontinuity, or a commercial insertion opportunity code.
 4. Theapparatus of claim 3, wherein the processor circuitry is to identify thechange in the box-formatting between the consecutive video frames bymonitoring for screen filler areas in edges in a video frame of theconsecutive video frames.
 5. The apparatus of claim 1, wherein theprocessor circuitry is to determine the aggregated weighted hint valueby: generating, based on a first weighting value and the first hintvalue, a first weighted hint value, the first weighting value based on afirst reliability of the first characteristic; generating, based on asecond weighting value and the second hint value, a second weighted hintvalue, the second weighting value based on a second reliability of thesecond characteristic; and determining the aggregated weighted hintvalue based on the first weighted hint value and the second weightedhint value.
 6. The apparatus of claim 1, wherein the processor circuitryis to indicate the presence of the commercial transition by transmittinga message indicative of the commercial transition to a commercialidentification system, the transmission of the message to cause thecommercial identification system to identify a commercial following thecommercial transition.
 7. The apparatus of claim 1, wherein the mediapresentation is associated with a monitored digital television feed. 8.A non-transitory computer readable medium comprising instructions that,when executed, cause at least one processor to at least: generate afirst hint value based on a first characteristic associated with a mediapresentation, the first characteristic indicative of a commercialtransition; generate a second hint value based on a secondcharacteristic associated with the media presentation, the secondcharacteristic indicative of the commercial transition; determine anaggregated weighted hint value based on the first hint value and thesecond hint value; and indicate a presence of the commercial transitionassociated with the media presentation based on a determination that theaggregated weighted hint value satisfies a threshold.
 9. Thenon-transitory computer readable medium of claim 8, wherein thethreshold is a first threshold, the first characteristic is an amount ofaudio randomness in an inter-segment audio frame of the mediapresentation, and the instructions are to cause the at least oneprocessor to: determine the amount of audio randomness being based on arandom-factor ratio; and generate the first hint value based on acomparison of the amount of audio randomness to a second threshold. 10.The non-transitory computer readable medium of claim 8, wherein thesecond characteristic is a presence of at least one of a change inbox-formatting between consecutive video frames, an audio format change,an aspect ratio change, a timestamp discontinuity, a closed-captioningtext discontinuity, or a commercial insertion opportunity code.
 11. Thenon-transitory computer readable medium of claim 10, wherein theinstructions are to cause the at least one processor to identify thechange in the box-formatting between the consecutive video frames bymonitoring for screen filler areas in edges in a video frame of theconsecutive video frames.
 12. The non-transitory computer readablemedium of claim 8, wherein the instructions are to cause the at leastone processor to: generate, based on a first weighting value and thefirst hint value, a first weighted hint value, the first weighting valuebased on a first reliability of the first characteristic; generate,based on a second weighting value and the second hint value, a secondweighted hint value, the second weighting value based on a secondreliability of the second characteristic; and determine the aggregatedweighted hint value based on the first weighted hint value and thesecond weighted hint value.
 13. The non-transitory computer readablemedium of claim 8, wherein the instructions are to cause the at leastone processor to transmit a message indicative of the commercialtransition to a commercial identification system, the transmission ofthe message to cause the commercial identification system to identify acommercial following the commercial transition.
 14. The non-transitorycomputer readable medium of claim 8, wherein the media presentation isassociated with a monitored digital television feed.
 15. A methodcomprising: generating, by executing an instruction with a processor, afirst hint value based on a first characteristic associated with a mediapresentation, the first characteristic indicative of a commercialtransition; generating, by executing an instruction with the processor,a second hint value based on a second characteristic associated with themedia presentation, the second characteristic indicative of thecommercial transition; determining, by executing an instruction with theprocessor, an aggregated weighted hint value based on the first andsecond hint values; and indicating, by executing an instruction with theprocessor, a presence of the commercial transition associated with themedia presentation based on a determination that the aggregated weightedhint value satisfies a threshold.
 16. The method of claim 15, whereinthe threshold is a first threshold, the first characteristic is anamount of audio randomness in an inter-segment audio frame of the mediapresentation, and further including: determining the amount of audiorandomness being based on a random-factor ratio; and generating, byexecuting an instruction with the processor, the first hint value basedon a comparison of the amount of audio randomness to a second threshold.17. The method of claim 15, wherein the second characteristic is apresence of at least one of a change in box-formatting betweenconsecutive video frames, an audio format change, an aspect ratiochange, a timestamp discontinuity, a closed-captioning textdiscontinuity, or a commercial insertion opportunity code.
 18. Themethod of claim 17, further including identifying the change in thebox-formatting between the consecutive video frames by monitoring forscreen filler areas in edges in a video frame of the consecutive videoframes.
 19. The method of claim 15, further including: generating, basedon a first weighting value and the first hint value, a first weightedhint value, the first weighting value based on a first reliability ofthe first characteristic; generating, on a second weighting value andthe second hint value, a second weighted hint value, the secondweighting value based on a second reliability of the secondcharacteristic; and determining the aggregated weighted hint value basedon the first weighted hint value and the second weighted hint value. 20.The method of claim 15, further including transmitting a messageindicative of the commercial transition to a commercial identificationsystem, the transmission of the message to cause the commercialidentification system to identify a commercial following the commercialtransition.